TABLE 7.
Task | Data set | Competitive methods | K-means solution | |||
---|---|---|---|---|---|---|
CSPA | HCC | PTGP | KCC | |||
Consensus clusteringwith utility function | iris | 1.34 | 4.57 | 285 | 0.29 | |
cranmed | 5.27 | 105.41 | 35.76 | 0.44 | ||
hitech | 4.77 | 102.93 | 36.93 | 0.43 | ||
k1b | 5.66 | 119.36 | 35.27 | 0.21 | ||
mm | 6.57 | 112.34 | 10.61 | 0.14 | ||
CSPA | HCC | PTGP | SEC | |||
Consensus clusteringwith co-association matrix | cacmcisi | 18.55 | 543.20 | 117.69 | 0.25 | |
classic | 32.14 | 1640.71 | 524.76 | 0.62 | ||
la12 | 21.48 | 1148.17 | 44.27 | 0.17 | ||
reviews | 10.97 | 397.16 | 26.89 | 0.12 | ||
wine | 0.83 | 4.57 | 2.85 | 0.05 | ||
CNMF | LCVQE | KCC | PLCC | |||
Constrained clustering | breast | 0.43 | 0.05 | 0.27 | 0.01 | |
ecoli | 0.19 | 0.03 | 0.22 | 0.01 | ||
iris | 0.13 | 0.01 | 0.07 | 0.01 | ||
pendigits | 195.38 | 76.73 | 4.98 | 0.45 | ||
satimage | 0.05 | 0.01 | 0.10 | 0.01 | ||
LOF | FABOD | iForest | BP | COR | ||
Outlier detection | caltech | 13.69 | 140.68 | 6.91 | 12.86 | 0.14 |
fbis | 17.54 | 1319.21 | 12.60 | 15.66 | 0.38 | |
re1 | 16.86 | 738.22 | 8.50 | 20.03 | 0.10 | |
wap | 26.81 | 1811.28 | 8.53 | 36.58 | 0.19 | |
yeast | 0.09 | 3.44 | 4.35 | 0.28 | 0.03 |
Note: All the algorithms in the above table were implemented by MATLAB and run on a Ubuntu 14.04 platform with Intel Core i7-6900K @ 3.2GHz and 64 GB RAM.